The therapy relationship, digital interventions, and their interaction.

This article serves as an introduction to a special section devoted to the psychotherapy relationship and digital interventions. The nature of the therapy relationship is explored, and the question is raised as to whether machines can have relationships with their users. Finally, an overview and synthesis of the articles in the special section is provided.

Savoring changes novel positive mindset targets of GAD treatment: Optimism, prioritizing positivity, kill-joy thinking, and worry mediation.

This study analyzed effects of savoring on unstudied positive mindset targets of generalized anxiety disorder (GAD) treatment (ClinicalTrials.gov: NCT05040061). 85 students with GAD were randomly assigned to one of two ecological momentary interventions (EMIs) on smartphone for seven days. The SkillJoy EMI promoted practices for savoring positive emotions. An active control EMI mirrored SkillJoy, yet did not include savoring or positive emotion. Optimism, worry, kill-joy thinking (lessening positive emotion with cognition), and prioritization of positive emotion activities and goals were assessed at pre-trial, eighth-day, post-trial, and 30th-day follow-up. Savoring was assessed pre-trial and fifth-day mid-trial. Longitudinal linear mixed models and simple slope analyses examined change between and within conditions. Bias-corrected bootstrapping path analysis examined mediation of worry change by increased savoring. SkillJoy led to significantly greater increases in both optimism and prioritizing positivity than the control from pre-trial to post-trial and pre-trial to follow-up. Both interventions significantly reduced kill-joy thinking at both timepoints with Skilljoy leading to marginally greater change at post-trial. Pre- to mid-trial increases in savoring mediated the relationships between treatment condition and reductions in worry at both post-trial and follow-up.

Is a brief mindfulness ecological momentary intervention more efficacious than a self-monitoring app for social anxiety disorder? A randomized controlled trial.

Despite their proliferation, limited knowledge exists regarding possible benefits of brief mindfulness ecological momentary interventions (MEMIs) for social anxiety disorder (SAD). Propositions that MEMIs could alleviate SAD symptoms and related clinical outcomes remain untested. This trial evaluated a 14-day MEMI for SAD. Participants with self-reported SAD were randomized to MEMI (n = 96) or self-monitoring app (SM; n = 95). Whereas MEMI instructed mindfulness exercises, SM prompted only self-monitoring five times daily for 14 days. Participants completed state-level self-reports of depression, anxiety, and mindfulness pre-post-mindfulness practice and SAD symptoms, worry, depression severity, repetitive negative thinking, and trait mindfulness at pre-randomization, post-intervention, and 1-month follow-up (1MFU). Hierarchical linear modeling was conducted. The MEMI yielded statistically significantly larger improvements in momentary depression, anxiety, and mindfulness (Cohen's d = -0.10-0.11). Although no between-group effects emerged in alleviating SAD fear and avoidance, excessive worry, depression severity, repetitive negative thinking, and trait mindfulness (-0.13-0.15), within-group effects were significantly small-to-large from pre-post and pre-1MFU (-4.62-0.67). A significant reduction in depression severity occurred in MEMI (-0.63--0.60) but not SM (-0.31--0.29). Brief MEMI and SM yielded nondifferent sustained effects on SAD, comorbid symptoms, and risk factors, highlighting its potential value within stepped-care delivery settings.

Testing the Efficacy of a Brief, Self-Guided Mindfulness Ecological Momentary Intervention on Emotion Regulation and Self-Compassion in Social Anxiety Disorder: Randomized Controlled Trial.

BACKGROUND: Theories propose that brief, mobile, self-guided mindfulness ecological momentary interventions (MEMIs) could enhance emotion regulation (ER) and self-compassion. Such changes are posited to be mechanisms of change. However, rigorous tests of these theories have not been conducted. OBJECTIVE: In this assessor-blinded, parallel-group randomized controlled trial, we aimed to test these theories in social anxiety disorder (SAD). METHODS: Participants with SAD (defined as having a prerandomization cut-off score ≥20 on the Social Phobia Inventory self-report) were randomized to a 14-day fully self-guided MEMI (96/191, 50.3%) or self-monitoring app (95/191, 49.7%) arm. They completed web-based self-reports of 6 clinical outcome measures at prerandomization, 15-day postintervention (administered the day after the intervention ended), and 1-month follow-up time points. ER and self-compassion were assessed at preintervention and 7-day midintervention time points. Multilevel modeling determined the efficacy of MEMI on ER and self-compassion domains from pretrial to midintervention time points. Bootstrapped parallel multilevel mediation analysis examined the mediating role of pretrial to midintervention ER and self-compassion domains on the efficacy of MEMI on 6 clinical outcomes. RESULTS: Participants demonstrated strong compliance, with 78% (149/191) engaging in at least 80% of the MEMI and self-monitoring prompts. MEMI was more efficacious than the self-monitoring app in decreasing ER goal-directed behavior difficulties (between-group Cohen d=-0.24) and lack of emotional clarity (Cohen d=0.16) and increasing self-compassion social connectedness (Cohen d=0.19), nonidentification with emotions (Cohen d=0.16), and self-kindness (Cohen d=0.19) from pretrial to midintervention time points. The within-group effect sizes from pretrial to midintervention were larger in the MEMI arm than in the self-monitoring app arm (ER goal-directed behavior difficulties: Cohen d=-0.73 vs -0.29, lack of emotional clarity: Cohen d=-0.39 vs -0.21, self-compassion domains of social connectedness: Cohen d=0.45 vs 0.19, nonidentification with emotions: Cohen d=0.63 vs 0.48, and self-kindness: Cohen d=0.36 vs 0.10). Self-monitoring, but not MEMI, alleviated ER emotional awareness issues (between-group Cohen d=0.11 and within-group: Cohen d=-0.29 vs -0.13) and reduced self-compassion acknowledging shared human struggles (between-group Cohen d=0.26 and within-group: Cohen d=-0.23 vs 0.13). No ER and self-compassion domains were mediators of the effect of MEMI on SAD symptoms (P=.07-<.99), generalized anxiety symptoms (P=.16-.98), depression severity (P=.20-.94), repetitive negative thinking (P=.12-.96), and trait mindfulness (P=.18-.99) from pretrial to postintervention time points. Similar nonsignificant mediation effects emerged for all of these clinical outcomes from pretrial to 1-month follow-up time points (P=.11-.98). CONCLUSIONS: Brief, fully self-guided, mobile MEMIs efficaciously increased specific self-compassion domains and decreased ER difficulties associated with goal pursuit and clarity of emotions from pretrial to midintervention time points. Higher-intensity MEMIs may be required to pinpoint the specific change mechanisms in ER and self-compassion domains of SAD. TRIAL REGISTRATION: Open Science Framework (OSF) Registries; osf.io/m3kxz https://osf.io/m3kxz.

Machine Learning and Bayesian Network Analyses Identifies Psychiatric Disorders and Symptom Associations with Insomnia in a national sample of 31,285 Treatment-Seeking College Students.

Background: A better understanding of the structure of relations among insomnia and anxiety, mood, eating, and alcohol-use disorders is needed, given its prevalence among young adults. Supervised machine learning provides the ability to evaluate the discriminative accuracy of psychiatric disorders associated with insomnia. Combined with Bayesian network analysis, the directionality between symptoms and their associations may be illuminated. Methods: The current exploratory analyses utilized a national sample of college students across 26 U.S. colleges and universities collected during population-level screening before entering a randomized controlled trial. Firstly, an elastic net regularization model was trained to predict, via repeated 10-fold cross-validation, which psychiatric disorders were associated with insomnia severity. Seven disorders were included: major depressive disorder, generalized anxiety disorder, social anxiety disorder, panic disorder, post-traumatic stress disorder, anorexia nervosa, and alcohol use disorder. Secondly, using a Bayesian network approach, completed partially directed acyclic graphs (CPDAG) built on training and holdout samples were computed via a Bayesian hill-climbing algorithm to determine symptom-level interactions of disorders most associated with insomnia [based on SHAP (SHapley Additive exPlanations) values)] and were evaluated for stability across networks. Results: Of 31,285 participants, 20,597 were women (65.8%); mean (standard deviation) age was 22.96 (4.52) years. The elastic net model demonstrated clinical significance in predicting insomnia severity in the training sample [R2 = .449 (.016); RMSE = 5.00 [.081]), with comparable performance in accounting for variance explained in the holdout sample [R2 = .33; RMSE = 5.47). SHAP indicated the presence of any psychiatric disorder was associated with higher insomnia severity, with major depressive disorder demonstrated to be the most associated disorder. CPDAGs showed excellent fit in the holdout sample and suggested that depressed mood, fatigue, and self-esteem were the most important depression symptoms that presupposed insomnia. Conclusion: These findings offer insights into associations between psychiatric disorders and insomnia among college students and encourage future investigation into the potential direction of causality between insomnia and major depressive disorder. Trial registration: Trial may be found on the National Institute of Health RePORTER website: Project Number: R01MH115128-05.

Nurturing innovation, catalyzing change: Honoring the legacy of Dr. C. Barr Taylor in the eating disorders field.

This Virtual Issue of the International Journal of Eating Disorders honors the legacy of the late Dr. C. Barr Taylor in the eating disorders (EDs) field. For decades, Dr. Taylor led the way in not only conducting the research needed to achieve the ultimate goal of making affordable, accessible, and evidence-based care for EDs available to all, but also nurturing the next generation of scientific leaders and innovators. Articles included in this Virtual Issue are a selection of Dr. Taylor's published works in the Journal in the past decade, spanning original research, ideas worth researching, commentaries, and a systematic review. We hope this Virtual Issue will inspire the next generation of research in EDs, and equally, if not more importantly, the next generation of young investigators in the field. We urge the field to continue and build upon Dr. Taylor's vision-to increase access to targeted prevention and intervention for EDs in innovative and forward-thinking ways-while embracing his unique and powerful mentorship style to lift up early career investigators and create a community of leaders to address and solve our field's biggest challenges.

Elevated depression and anxiety predict future patterns of individualistic and collectivistic cultural values: A cross-lagged longitudinal network analysis.

BACKGROUND: Specific components of independent and interdependent self-construal have been associated with psychopathology. However, most studies on this topic have been cross-sectional, precluding causal inferences. We used contemporaneous and temporal cross-lagged network analysis to establish weak causal effects in understanding the association between self-construal and psychopathology components. METHODS: Middle-aged and older community-dwelling adults (n = 3294) participated in the Midlife Development in the United States study across two time-points, spaced nine years apart. Six self-construal (interdependence: connection to others, commitment to others, receptiveness to influence; independence: behavioral consistency, sense of difference from others, self-reliance) and three psychopathology nodes (major depressive disorder (MDD), generalized anxiety disorder (GAD), and panic disorder (PD) symptom severity) were examined. All network analyses controlled for age, sex, race, and number of chronic illnesses as covariates. RESULTS: Contemporaneous and temporal networks yielded relations between elevated MDD and PD and increased receptiveness to influence. Heightened GAD symptom severity was associated with future increased difference from others and decreased connection to others, commitment to others, and receptiveness to influence. Higher MDD, GAD, and PD severity were associated with future lower self-reliance. Network comparison tests revealed no consistent network differences across sex and race. LIMITATIONS: DSM-III-R measures of MDD, GAD, and PD were used. Results may not generalize to culturally diverse racial groups. CONCLUSIONS: Changes in self-construal may result from increased MDD, GAD, and PD severity. Findings suggest the importance of targeting common mental health symptoms to positively influence how individuals view the self and others in various social contexts.

Positive reappraisal coping mediates the relationship between parental abuse and lack of affection on adulthood generalized anxiety severity.

Exposure to parental abuse and lack of parental affection during childhood are risk factors for adulthood psychopathology. Tendency to engage in positive reappraisal may be a plausible mechanism underlying this relationship. The current study examined if positive reappraisal coping mediated the relationship between maternal/paternal abuse/affection and adulthood generalized anxiety disorder (GAD) symptoms. Participant data (N = 3294) from the Midlife Development in the United States study was collected in three waves, spaced nine years apart. Longitudinal structural equation mediation modeling examined whether positive reappraisal coping at Time 2 mediated the relationship between maternal/paternal abuse/affection at Time 1 and GAD symptoms at Time 3, controlling for GAD symptoms at Time 1. Positive reappraisal coping mediated maternal/paternal childhood abuse - GAD symptom severity and maternal/paternal childhood affection - GAD severity relations. Maternal and paternal abuse was associated with lower positive reappraisal tendencies, predicting increased GAD symptom severity. Conversely, higher maternal/paternal affection was associated with increased positive reappraisal, predicting lower GAD severity. Incremental prediction revealed that childhood abuse to GAD severity via positive reappraisal path was significant for maternal but not paternal abuse, whereas affection from both parents remained significant. Positive reappraisal coping may be a possible mechanism linking childhood experiences to adulthood GAD severity.

Internalizing psychopathology and its links to suicidal ideation, dysfunctional attitudes, and help-seeking readiness in a national sample of college students.

BACKGROUND: Recent evidence suggests that multiple emotional disorders may be better assessed using dimensional models of psychopathology. The current study utilized a cross-sectional population survey of college students (N = 8613 participants) to examine the extent to which broad psychopathology factors accounted for specific associations between emotional problems and clinical and behavioral validators: suicidality, dysfunctional attitudes, and treatment seeking. METHODS: Confirmatory factor models were estimated to identify the best structure of psychopathology. Models were then estimated to examine the broad and specific associations between each psychopathology indicator and the clinical and behavioral validators. RESULTS: The hierarchical model of psychopathology with internalizing problems at the top, fear, and distress at the second level, and five specific symptom dimensions at the third level evidenced the best fit. The associations between symptom indicators of psychopathology and clinical and behavioral validators were relatively small and inconsistent. Instead, much of the association between clinical and behavioral validators and emotional problems operated at a higher-order level. LIMITATIONS: The cross-sectional nature of the survey precludes the ability to make conclusions regarding causality. CONCLUSIONS: Researchers should focus on investigating the shared or common components across emotional disorders, particularly concerning individuals presenting with higher rates of suicidal ideation dysfunctional attitudes, and help-seeking behavior. Using higher-order dimensions of psychopathology could simplify the complex presentation of multiple co-occurring disorders and suggest valid constructs for future investigations.

Introduction to a special issue on the contrast avoidance model.

The current paper introduces the special issue on the Contrast Avoidance Model. The Contrast Avoidance Mmodel theorizes that chronic worriers are afraid of a sharp increase in negative emotion and/or sharp reduction in positive emotion (labeled negative emotional contrasts; NECs). They thus use perseverative thought as means to create and sustain negative emotion to prevent NECs if they were to experience negative events. Further, these individuals are uncomfortable with sustained positive emotion because it leaves them vulnerable to NECs. At the same time, worry increases the probability of positive emotional contrasts (PECs), or sharp increases in positive emotion or decreases in negative emotion when things turn out better than expected or positive events are experienced. Therefore, these individuals generate negative emotion via perseverative thought as a way to avoid NECs and increase the likelihood of PECs. The current special issue provides novel research on the model.

The Contrast Avoidance Model: Conclusion and synthesis of new research in the special issue.

In this special series, new research on the Contrast Avoidance Model (CAM) was presented, including studies on the role of CAM in the maintenance of chronic worry, the incremental validity of CAM, CAM as a mediator of the association between generalized anxiety disorder (GAD) and other variables, CAM as transdiagnostic, and interpersonal behaviors as a means to avoid negative emotional contrasts (NECs). Furthermore, the role of perseverative thought in relation to positive emotional contrasts (PECs) was explored. Studies indicated that higher worry was positively and negatively reinforced, a factor that is likely to contribute to the maintenance of GAD. Further, research demonstrated that CAM contributed unique variance to understanding GAD above and beyond other variables associated with GAD, such as intolerance of uncertainty and negative problem orientation. Additional research revealed the transdiagnostic nature of contrast avoidance, as well as the association between contrast avoidance and problem-solving deficits. In addition, both worry and rumination increased the likelihood of PECs. Further, data suggested that anxious individuals may use interpersonal strategies to avoid NECs. Finally, savoring positive emotions was found to reduce contrast avoidance, providing a novel intervention strategy to address contrast avoidance in individuals with GAD.

Which client with generalized anxiety disorder benefits from a mindfulness ecological momentary intervention versus a self-monitoring app? Developing a multivariable machine learning predictive model.

Precision medicine methods (machine learning; ML) can identify which clients with generalized anxiety disorder (GAD) benefit from mindfulness ecological momentary intervention (MEMI) vs. self-monitoring app (SM). We used randomized controlled trial data of MEMI vs. SM for GAD (N = 110) and tested three ML models to predict one-month follow-up reliable improvement in GAD severity, perseverative cognitions (PC), trait mindfulness (TM), and executive function (EF). Eleven baseline predictors were tested regarding differential reliable change from MEMI vs. SM (age, sex, race, EF errors, inhibitory dyscontrol, set-shifting deficits, verbal fluency, working memory, GAD severity, TM, PC). The final top five prescriptive predictor models of all outcomes performed well (AUC = .752 .886). The following variables predicted better outcome from MEMI vs. SM: Higher GAD severity predicted more GAD improvement but less EF improvement. Elevated PC, inhibitory dyscontrol, and verbal dysfluency predicted better improvement in most outcomes. Greater set-shifting and TM predicted stronger improvements in GAD symptoms and TM. Older age predicted more alleviation of GAD and PC symptoms. Women exhibited more enhancements in trait mindfulness and EF than men. White individuals benefitted more than non-White. PC, TM, EF, and sociodemographic data might help predictive models optimize intervention selection for GAD.

CATCH-ON Connect: a tablet intervention to address social isolation and loneliness.

Technology can aid in alleviating social isolation and loneliness among older adults, however some older adults lack the knowledge and necessary skills to use the technology. OBJECTIVES: The purpose of this study was to examine the impact of CATCH-ON Connect, a cellular enabled tablet technical assistance program, on social isolation and loneliness among older adults. METHODS: This is a single-group pre-post program evaluation of the CATCH-ON Connect program. RESULTS: While there was no statistically significant change in social isolation, older adult participants reported significantly lower levels of loneliness following intervention. CONCLUSION: This project demonstrates that tablet programs with technical assistance may benefit older adults. Further investigation is warranted to determine the impact of the internet access itself, the technical assistance, or both.

Training, supervision, and experience of coaches offering digital guided self-help for mental health concerns.

Accessible, low-cost intervention options are necessary to address the rise in mental health problems among college students. Digital guided self-help, or coached, programs have been developed to provide such services, with many commercially available. As such, there are a large and growing number of individuals coaching these programs. However, an unmet need is to evaluate and assess best practices for training and supervising individuals in these positions. To this end, we describe how we recruited, trained, and supervised coaches as part of a large randomized controlled trial using a widely available digital commercial platform. Coaches were trained to provide digital guided self-help for depression, anxiety, and/or eating disorders for college students. Coaches initially attended three live training sessions over 2-3 weeks, viewed multiple training videos, and read a detailed coaching manual developed by our team. Thereafter, they attended weekly supervision. Following their term, coaches completed an exit survey to assess their supervision and training experiences. A total of 37 of 70 (53%) graduate-level student coaches completed the survey. The experience was reported as very positive (95%). In particular, the majority reported feeling well prepared, more confident, and felt they had developed useful skills for their own practice.

Using Social Influence Strategies to Improve Rates of Online Mental Health Survey Participation: Results from Two Experiments.

Online surveys are routinely used in mental health screening and treatment follow-up assessment, though they can yield low response rates. We tested the effects of social psychology-informed influence strategies for increasing rates of participation in an online mental health screening survey (Experiment 1) and a treatment follow-up survey (Experiment 2). In Experiment 1 (N = 45,569), embedding one or any combination of three motivational appeals (personal gain, community gain, and inclusivity) in screening survey invitation and reminder emails unexpectedly led to lower rates of survey participation compared to when the appeals were not included (overall participation rate = 12.02%, ORs = 0.75 to 0.97, ps < .001). In Experiment 2 (N = 873), a video of a TikTok influencer encouraging survey participation embedded in treatment follow-up survey invitation and reminder emails did not significantly affect survey completion compared to a humorous gif unrelated to survey participation (overall participation rate = 47.88%, OR = 1.18, p = .200). Moderator analyses revealed that the video led to higher rates of participation than the gif among White participants (OR = 1.39, p = .031) and non-Hispanic participants (OR = 1.35, p = .029) only, whereas the video led to lower rates of participation than the gif among students who did not disclose their race (OR = 0.31, p = .010). Results suggested that efforts to improve online survey participation should be balanced with possible downsides (e.g., added email length) and should be evaluated for differential performance among population subgroups prior to widespread implementation.

Crossroads of Antimicrobial and Diagnostic Stewardship: Assessing Risks to Develop Clinical Decision Support to Combat Multidrug-Resistant Pseudomonas.

Background: Early detection of multidrug-resistant Pseudomonas aeruginosa (MDRP) remains challenging. Existing risk prediction tools are difficult to translate to bedside application. The goal of this study was to develop a simple electronic medical record (EMR)-integrated tool for prediction of MDRP infection. Methods: This was a mixed-methods study. We conducted a split-sample cohort study of adult critical care patients with P aeruginosa infections. Two previously published tools were validated using c-statistic. A subset of variables based on strength of association and ease of EMR extraction was selected for further evaluation. A simplified tool was developed using multivariable logistic regression. Both c-statistic and theoretical trade-off of over- versus underprescribing of broad-spectrum MDRP therapy were assessed in the validation cohort. A qualitative survey of frontline clinicians assessed understanding of risks for MDRP and potential usability of an EMR-integrated tool to predict MDRP. Results: The 2 previous risk prediction tools demonstrated similar accuracy in the derivation cohort (c-statistic of 0.76 [95% confidence interval {CI}, .69-.83] and 0.73 [95% CI, .66-.8]). A simplified tool based on 4 variables demonstrated reasonable accuracy (c-statistic of 0.71 [95% CI, .57-.85]) without significant overprescribing in the validation cohort. The risk factors were prior MDRP infection, ≥4 antibiotics prior to culture, infection >3 days after admission, and dialysis. Fourteen clinicians completed the survey. An alert providing context regarding individual patient risk factors for MDRP was preferred. Conclusions: These results can be used to develop a local EMR-integrated tool to improve timeliness of effective therapy in those at risk of MDRP infections.

Unlocking the Emotional World of Visual Media: An Overview of the Science, Research, and Impact of Understanding Emotion: Drawing Insights From Psychology, Engineering, and the Arts, This Article Provides a Comprehensive Overview of the Field of Emotion Analysis in Visual Media and Discusses the Latest Research, Systems, Challenges, Ethical Implications, and Potential Impact of Artificial Emotional Intelligence on Society.

The emergence of artificial emotional intelligence technology is revolutionizing the fields of computers and robotics, allowing for a new level of communication and understanding of human behavior that was once thought impossible. While recent advancements in deep learning have transformed the field of computer vision, automated understanding of evoked or expressed emotions in visual media remains in its infancy. This foundering stems from the absence of a universally accepted definition of "emotion," coupled with the inherently subjective nature of emotions and their intricate nuances. In this article, we provide a comprehensive, multidisciplinary overview of the field of emotion analysis in visual media, drawing on insights from psychology, engineering, and the arts. We begin by exploring the psychological foundations of emotion and the computational principles that underpin the understanding of emotions from images and videos. We then review the latest research and systems within the field, accentuating the most promising approaches. We also discuss the current technological challenges and limitations of emotion analysis, underscoring the necessity for continued investigation and innovation. We contend that this represents a "Holy Grail" research problem in computing and delineate pivotal directions for future inquiry. Finally, we examine the ethical ramifications of emotion-understanding technologies and contemplate their potential societal impacts. Overall, this article endeavors to equip readers with a deeper understanding of the domain of emotion analysis in visual media and to inspire further research and development in this captivating and rapidly evolving field.

Associations between mitochondrial biomarkers, urban residential exposures and childhood asthma outcomes over 6 months.

Determining biomarkers of responses to environmental exposures and evaluating whether they predict respiratory outcomes may help optimize environmental and medical approaches to childhood asthma. Relative mitochondrial (mt) DNA abundance and other potential mitochondrial indicators of oxidative stress may provide a sensitive metric of the child's shifting molecular responses to its changing environment. We leveraged two urban childhood cohorts (Environmental Control as Add-on Therapy in Childhood Asthma (ECATCh); Columbia Center for Children's Environmental Health (CCCEH)) to ascertain whether biomarkers in buccal mtDNA associate with airway inflammation and altered lung function over 6 months of time and capture biologic responses to multiple external stressors such as indoor allergens and fine particulate matter (PM2.5). Relative mtDNA content was amplified by qPCR and methylation of transfer RNA phenylalanine/rRNA 12S (TF/RNR1), cytochrome c oxidase (CO1), and carboxypeptidase O (CPO) was measured by pyrosequencing. Data on residential exposures and respiratory outcomes were harmonized between the two cohorts. Repeated measures and multiple regression models were utilized to assess relationships between mitochondrial biomarkers, respiratory outcomes, and residential exposures (PM2.5, allergens), adjusted for potential confounders and time-varying asthma. We found across the 6 month visits, a 0.64 fold higher level of TF/RNR1 methylation was detected among those with asthma in comparison to those without asthma ((parameter estimate (PE) 0.64, standard error 0.28, p = 0.03). In prospective analyses, CPO methylation was associated with subsequent reduced forced vital capacity (FVC; PE -0.03, standard error 0.01, p = 0.02). Bedroom dust mouse allergen, but not indoor PM2.5, was associated with higher methylation of TF/RNR1 (PE 0.015, standard error 0.006, p = 0.01). Select mtDNA measures in buccal cells may indicate children's responses to toxic environmental exposures and associate selectively with asthma and lung function.